Dive Brief:
- Talent gaps and technology hurdles are hindering strategic adoption of generative AI capabilities, according to a Pluralsight report published Thursday. The IT workforce training company surveyed 600 technology decision-makers.
- While two-thirds of respondents said their organization had short-term AI plans in place, only one-third have a long-term adoption strategy. Over half of respondents pointed to a lack of fully mature data systems to handle AI’s technical and operational demands.
- “There is a critical gap between organizational ambition and actual readiness when it comes to AI adoption,” Chris McClellen, chief product and technology officer at Pluralsight, said in an announcement Thursday. “While many companies recognize the importance of AI, the lack of long-term strategies, mature systems, and comprehensive workforce upskilling to support the demands of AI leaves them unable to capitalize on its potential.”
Dive Insight:
Generative AI tested the mettle of enterprise data systems and technology skills, exposing weaknesses on both counts across industries. CIOs responded by doubling down on AI talent recruitment and upskilling initiatives, as data hardware and infrastructure spending spiked.
Efforts to lay the groundwork for AI adoption have yielded mixed results so far, according to Pluralsight. Two-thirds of respondents said more than half of their workforce had well-developed AI skills, yet three-quarters reported pausing or delaying AI projects for lack of sufficient talent.
Two years after ChatGPT’s arrival, many enterprises anxiously awaited signs of a return on generative AI investments. More than one-third of companies succeeded in scaling generative AI use cases as of last year, according to an Accenture survey of 3,450 C-suite leaders published Thursday. But a mere 13% said the technology had created significant value.
While many organizations have yet to overcome data readiness, process redesign and C-suite sponsorship challenges, the banking and insurance industries have had success scaling domain-specific AI applications with measurable ROI, the professional services firm found.
Successful deployment of AI assistants, chatbots and a new generation of agentic tools takes targeted and sustained investment in workforce and technology modernization.
Manulife Financial rolled out a proprietary generative AI assistant called ChatMFC across its global workforce after a decade of active investment in AI capabilities, the insurer said in a Thursday announcement.
The company has poured billions into building out its digital capabilities through investments in a cloud-based data and AI platform, an AI skills building program and a team of 200 data scientists and machine learning engineers.
“We’ve doubled our AI-driven impact by diversifying and expanding solutions, strengthening data and AI platforms and practicing responsible AI governance,” Manulife Global Chief Analytics Officer Jodie Wallis said in the announcement.
The company said it expects a three-fold return over five years on its AI investments.
Sparking sustained spend on the technology remains a hurdle for many companies. More than half of respondents to Pluralsight’s survey said their organization has directed less than $500,000 into AI initiatives.
A clear line-of-sight to ROI is clouded by scope and magnitude of the investments required, according to Nagendra Bandaru, managing partner and global head of Wipro Enterprise Futuring. IT executives are facing a three-headed beast on the path to adoption as they grapple with legacy system complexity, broken processes and masses of unclean data, Bandaru told CIO Dive.
“You have to solve for all three for AI to work seamlessly and give you a return on your investment,” he said.
